I. Novikov, A. Makarov, A. Pirogov, V. Podlipnov, A. Nikonorov, R. Skidanov, V. Platonov, V. Lobanov, Yu. Pridanova, Yu. Vybornova, O. Kalashnikova, T. Podladchikova
{"title":"Analysis of Hyperspectral Images of River Waters","authors":"I. Novikov, A. Makarov, A. Pirogov, V. Podlipnov, A. Nikonorov, R. Skidanov, V. Platonov, V. Lobanov, Yu. Pridanova, Yu. Vybornova, O. Kalashnikova, T. Podladchikova","doi":"10.3103/S1060992X24700668","DOIUrl":null,"url":null,"abstract":"<p>This article proposes an approach to the analysis of high-resolution hyperspectral images in the applied problem of analyzing the state of river waters. This method allows you to detect blooming or contamination of water by foreign substances. High-resolution hyperspectral images were obtained using a hyperspectrometer mounted on a small unmanned aerial vehicle. The difference between the spectra of river areas with different intensity of algal blooms is demonstrated. Samples of river water were taken, chemical analysis was carried out, which confirmed the different content of magnesium and calcium in all samples, corresponding to the intensity of algal blooms in the water. The effectiveness of using machine learning algorithms and the construction of index images for the classification of water areas with different intensity of algal blooms is shown.</p>","PeriodicalId":721,"journal":{"name":"Optical Memory and Neural Networks","volume":"33 2 supplement","pages":"S386 - S397"},"PeriodicalIF":1.0000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Memory and Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S1060992X24700668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
Abstract
This article proposes an approach to the analysis of high-resolution hyperspectral images in the applied problem of analyzing the state of river waters. This method allows you to detect blooming or contamination of water by foreign substances. High-resolution hyperspectral images were obtained using a hyperspectrometer mounted on a small unmanned aerial vehicle. The difference between the spectra of river areas with different intensity of algal blooms is demonstrated. Samples of river water were taken, chemical analysis was carried out, which confirmed the different content of magnesium and calcium in all samples, corresponding to the intensity of algal blooms in the water. The effectiveness of using machine learning algorithms and the construction of index images for the classification of water areas with different intensity of algal blooms is shown.
期刊介绍：
The journal covers a wide range of issues in information optics such as optical memory, mechanisms for optical data recording and processing, photosensitive materials, optical, optoelectronic and holographic nanostructures, and many other related topics. Papers on memory systems using holographic and biological structures and concepts of brain operation are also included. The journal pays particular attention to research in the field of neural net systems that may lead to a new generation of computional technologies by endowing them with intelligence.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
